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The Explanation Dialogues: understanding how legal experts reason about XAI methods

The Explanation Dialogues: understanding how legal experts reason about XAI methods
The Explanation Dialogues: understanding how legal experts reason about XAI methods

The Explanation Dialogues project is an expert focus study that aims to uncover expectations, reasoning, and rules of legal experts and practitioners towards explainable artificial intelligence (XAI). We examine legal perceptions and disputes that arise in a fictional scenario that resembles a daily life situation - a bank’s use of an automated decision-making (ADM) system to decide on credit allocation to individuals. Through this simulation, the study aims to provide insights into the legal value and validity of explanations of ADMs, identify potential gaps and issues that may arise in the context of compliance with European legislation, and provide guidance on how to address these shortcomings.

AI, Automated Decision-Making, Explainability, General Data Protection Regulation
State, Laura
01609949-a874-4a56-93b4-3f43d04c416b
Colmenarejo, Alejandra Bringas
26da6380-e442-41d8-b06d-554e3b7252ea
Beretta, Andrea
fa9fdb63-8fbf-4cc8-9e86-79dd280a8065
Ruggieri, Salvatore
1b1c73e9-3462-48d2-9864-e395c4daf337
Turini, Franco
4d637b00-8f5e-4164-a237-b543f4078879
Law, Stephanie
0778fc4b-cdf4-436e-9fcb-7f2ee2006ca4
State, Laura
01609949-a874-4a56-93b4-3f43d04c416b
Colmenarejo, Alejandra Bringas
26da6380-e442-41d8-b06d-554e3b7252ea
Beretta, Andrea
fa9fdb63-8fbf-4cc8-9e86-79dd280a8065
Ruggieri, Salvatore
1b1c73e9-3462-48d2-9864-e395c4daf337
Turini, Franco
4d637b00-8f5e-4164-a237-b543f4078879
Law, Stephanie
0778fc4b-cdf4-436e-9fcb-7f2ee2006ca4

State, Laura, Colmenarejo, Alejandra Bringas, Beretta, Andrea, Ruggieri, Salvatore, Turini, Franco and Law, Stephanie (2023) The Explanation Dialogues: understanding how legal experts reason about XAI methods. 2nd European Workshop on Algorithmic Fairness, EWAF 2023, , Winterthur, Switzerland. 07 - 09 Jun 2023.

Record type: Conference or Workshop Item (Paper)

Abstract

The Explanation Dialogues project is an expert focus study that aims to uncover expectations, reasoning, and rules of legal experts and practitioners towards explainable artificial intelligence (XAI). We examine legal perceptions and disputes that arise in a fictional scenario that resembles a daily life situation - a bank’s use of an automated decision-making (ADM) system to decide on credit allocation to individuals. Through this simulation, the study aims to provide insights into the legal value and validity of explanations of ADMs, identify potential gaps and issues that may arise in the context of compliance with European legislation, and provide guidance on how to address these shortcomings.

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More information

Published date: 7 June 2023
Additional Information: Funding Information: Work supported by the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie Actions for the project NoBIAS (g.a. No. 860630), and under the Excellent Science European Research Council (ERC) programme for the XAI project (g.a. No. 834756). This work reflects only the authors’ views and the European Research Executive Agency (REA) is not responsible for any use that may be made of the information it contains.
Venue - Dates: 2nd European Workshop on Algorithmic Fairness, EWAF 2023, , Winterthur, Switzerland, 2023-06-07 - 2023-06-09
Keywords: AI, Automated Decision-Making, Explainability, General Data Protection Regulation

Identifiers

Local EPrints ID: 487262
URI: http://eprints.soton.ac.uk/id/eprint/487262
PURE UUID: 55a6df21-3d39-4bc1-98a3-239f87cd89f4
ORCID for Alejandra Bringas Colmenarejo: ORCID iD orcid.org/0000-0002-7968-9853
ORCID for Stephanie Law: ORCID iD orcid.org/0000-0003-2551-7615

Catalogue record

Date deposited: 16 Feb 2024 17:15
Last modified: 30 Nov 2024 03:06

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Contributors

Author: Laura State
Author: Alejandra Bringas Colmenarejo ORCID iD
Author: Andrea Beretta
Author: Salvatore Ruggieri
Author: Franco Turini
Author: Stephanie Law ORCID iD

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